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TRANSCRIPT
PROJECT REPORT
INTERNET-CONNECTED, OCCUPANCY- RESPONSIVE, ADAPTIVE THERMOSTATS FOR
UNIVERSITY RESIDENCE HALLS
UC Davis, CA
June 2, 2014
WESTERN COOLING EFFICIENCY CENTER
OCCUPANCY RESPONSIVE THERMOSTATS 2 PROJECT REPORT
PREPARED FOR:Karl Johnson
California Institute for Energy & Environment
1333 Broadway, Suite 240
Oakland, CA
PREPARED BY:Jonathan Woolley
Associate Engineer
Marco Pritoni
Graduate Student Researcher
Paul Fortunato
Outreach Coordinator
Western Cooling Efficiency Center
University of California, Davis
215 Sage Street #100
Davis, CA 95616
wcec.ucdavis.edu
ABOUT THE WCECThe Western Cooling Efficiency Center was established along side the UC Davis Energy Efficiency Center in 2007 through a grant from the California Clean Energy Fund and in partnership with California Energy Commission Public Interest Energy Research Program. The Center partners with industry stakeholders to advance cooling-technology innovation by applying technologies and programs that reduce energy, water consumption and peak electricity demand associated with cooling in the Western United States.
ABOUT THE STATE PARTNERSHIP FOR ENERGY EFFICIENT DEMONSTRATIONS (SPEED) PROGRAMThe SPEED program is supported by the California Energy Commission and managed through the California Institute for Energy and Environment (CIEE). SPEED demonstrations are coordinated by the CIEE in partnership with the California Lighting Technology Center and the Western Cooling Efficiency Center, both at the University of California, Davis.
OCCUPANCY RESPONSIVE THERMOSTATS 3 PROJECT REPORT
Section Title Page
1.0 Executive Summary 4
2.0 About the Technology 5
3.0 Demonstrations at Segundo Housing Complex 7
4.0 Conclusions and Recommendations 10
5.0 Related Resources 12
6.0 Collaborators 13
TABLE OF CONTENTSSECTIONS
TABLES
Name Title Page
Table 1Review of recent studies on occupancy sensing
thermostats6
Table 2 Data periods utilized for this study 8
Table 3Savings calculated during academic and non-
academic periods
9
Table 4Performance results for both heating and cool-
ing modes during both high and low occupan-
cy levels
10
Figures
Name Title Page
Figure 1 Payback vs. Electricity Cost 10
OCCUPANCY RESPONSIVE THERMOSTATS 4 PROJECT REPORT
1.0 EXECUTIVE SUMMARY
Many recent field evaluations for communicating and
occupancy-responsive thermostats have shown sig-
nificant annual HVAC savings on the order of 10-20%.
However, the form and function for technologies in
this space vary widely.
Occupancy responsive thermostats adjust mechani-
cal system operating parameters to reduce energy
consumption when a conditioned space is vacant.
Unlike occupancy controls for lighting, the value
of occupancy control applied to heating and cool-
ing depends on a range of dynamic factors that are
difficult to measure and assess with precision. For
instance, the efficiency of heating and cooling equip-
ment changes with weather conditions and part-
or full-load runtime capacity, while thermal loads
depend on the aggressiveness of indoor temperature
set-points, and their dynamic relationship to a variety
of physical and environmental factors.
This report summarizes results from a series of
investigations with one type of occupancy sensing
adaptive thermostat installed in a number of resi-
dence halls at the University of California, Davis. The
technology tested automatically adjusts set-points
in each room during vacant periods and enables a
number of energy management services such as
central schedule control, and limitation of the user
set-point range.
Conclusions from the research are supported by the
findings that there is high variability for the tempera-
ture response and energy use between individual
rooms, and between different buildings. The potential
for energy savings during vacant periods is subject
to coincident meteorological conditions, however,
measuring these savings is complicated because
thermal loads associated with occupants themselves
may have a significant impact on energy use for
conditioning during vacant periods. Further, the mea-
sured savings for whole building chilled water energy
use appears to be greater for periods with low aver-
age building occupancy. Overall the study indicates
that considerable savings can be achieved in certain
instances, but that the impact is highly sensitive to
the specific technology implemented and
its application.
Segundo Housing Complex in Davis, California
OCCUPANCY RESPONSIVE THERMOSTATS 5 PROJECT REPORT
2.0 ABOUT THE TECHNOLOGY
Many buildings are often mechanically conditioned to a
constant set-point, regardless of whether they are oc-
cupied or not. Even in instances where set-points and
ventilation are scheduled, the pre-programmed operat-
ing times reflect assumed occupancy patterns and com-
fort preferences. In commercial and high rise residential
buildings, the same is true for mechanical ventilation.
This is a waste of energy and money, but has historically
been the only way to manage temperature and indoor air
quality without intensive manual regulation by users or
facilities managers.
The newest thermostat technologies capitalize on the
recent development of wireless communication proto-
cols, the proliferation of wireless communicating compo-
nents, and the infusion of the Internet into many aspects
of personal life and facility management. Thermostats
leverage these tools to enable much more sophisticated
control sequences. So-called ‘smart thermostats’ are
characterized generally by their communicating capabili-
ties, including web and mobile user interface options, as
well as networked control that allows for instantaneous
management of multiple thermostats in a facility. Smart
thermostats may include occupancy responsive con-
trol, adaptive or learning algorithms, demand response
capability, fault detection and diagnostics, and runtime
optimization features that impact equipment efficiency.
These features promise to improve usability, but more
importantly they provide automation for schedule and
set-point control which could optimize energy while
maintaining or improving overall comfort. However,
amidst the range of new and emerging thermostat tech-
nologies, it is not clear which features actually provide
energy savings, which improve level of service, which
enhance usability, or which are actually of little technical
value.
Building from programmable ‘set-back’ thermostats
and modern lighting controls, occupancy responsive
thermostats adjust operation for heating, cooling, and
ventilation when a space is unoccupied. Most occupancy
responsive thermostats do this by shifting the tempera-
ture back from the occupied temperature set-point. This
allows the room temperature to drift and should result
in reduced runtime for heating and cooling equipment.
In certain applications it may also reduce energy use re-
lated to ventilation. Generally, this adjustment is intended
to capture energy savings when no occupants are
detected while also maintaining a level of service (ther-
mal comfort, indoor air quality, sense of control) during
occupied periods. However, understanding the transition
from the unoccupied to the occupied state is critical for
predicting energy savings. When the set-point is re-
stored, additional energy must be expended for a period
of time to recover from the set-back. For example, if the
set-back and temperature drift occurs during a hot af-
ternoon, and recovery is in the evening, the energy saved
during the set-back period will be greater than energy
needed for recovery. There are also conditions for which
the energy for recovery exceeds the energy saved during
the set-back period. It has also been noted by others
that some set-back strategies may also result in periods
of unsatisfactory thermal comfort for occupants.
Adaptive controls automatically change operating pa-
rameters according to learned and predicted factors.
These systems adapt over time according to measured
responses. They can learn about system physical char-
acteristics (cooling capacity, temperature response
time, etc) and user schedules and preferences in order
Telkonet adaptive thermostat
OCCUPANCY RESPONSIVE THERMOSTATS 6 PROJECT REPORT
to predict appropriate set-back periods and ranges.
These features can save energy, improve thermal
comfort and/or improve convenience and user experi-
ence. These learning algorithms can be integrated with
features that respond to occupant proximity, or that
predict occupant comfort according to user feedback
and measured and forecast outdoor temperature.
Other StudiesSeveral recent studies on occupancy sensing thermo-
stats have concluded that, for the right application the
technologies offer significant savings (Table 1).
Description of Thermostat Features for Pilot EvaluationsThis study focuses on field evaluation of one occupancy
responsive adaptive thermostat technology provided by
Telkonet. The thermostat system learns about response
capabilities for the heating and cooling equipment and
automatically programs a set-back for vacant periods
that will allow for a timely recovery to the comfort set-
point when a room is again occupied.
The system studied communicates between multiple
thermostats on a ZigBEE mesh network, and uses a
central internet gateway to allow communication with
this network from a web-based user interface. Each ther-
mostat has an on-board (or remote wireless) infrared
motion detector. Vacancy in a room triggers adjustment
of the active set-point, which allows temperature to drift
and results in a reduced duty cycle for the conditioning
and ventilation systems. Additionally, the system incor-
porates an on-board light sensor and logic to distinguish
between vacancy and a nighttime condition where occu-
pants are sleeping. The system studied applies a learning
algorithm that continually adapts the set-back tempera-
ture for unoccupied periods so that a room can recover
within an acceptable period when an occupant returns.
During occupied periods, users are allowed temperature
control, although facility managers may limit the select-
able set-point range to avoid excessive heating or cool-
ing by residents.
Aside from the promise of energy savings, the technol-
ogy provides substantial value for facilities management
by providing central, web-based, on-demand control
of hundreds or thousands of rooms. Room-by-room
insight about instantaneous and historical system opera-
tion improves maintenance and troubleshooting capabil-
ities. Since the technology does not require integration
Type or Reference Author RUNTIME
Savings Link
Report HMG-CEC 12-24% Guest Room Occupancy Controls
Report PNNL 10-25% Guest Room HVAC Occupancy-Based Control Technology Demonstration
Report SDG&E ~20% Guest Room PTAC/PTHP Energy Management System
Press Release Telkonet 10%Networked Telkonet SmartEnergy Reinforces New York University’s
Sustainability Initiatives
Case Study Telkonet 38% Galt House Hotel
Case Study Telkonet 42% Radisson Hotel & Conference Center, Green Bay, Wisconsin
Case Study Telkonet 17-25% Habitat Suites Hotel, Austin, Texas
Table 1: Review of recent studies on occupancy sensing thermostats and key conclusions
OCCUPANCY RESPONSIVE THERMOSTATS 7 PROJECT REPORT
with the whole building equipment management system,
these features can be installed at a much lower cost than
would be required by a traditional wired approach.
3.0 DEMONSTRATIONSAs part of the State Partnership for Energy Efficient
Demonstrations, the Western Cooling Efficiency Cen-
ter collaborated with Student Housing and the Energy
Management Office at the University of California, Davis
to monitor and analyze the field performance of occupan-
cy-responsive adaptive thermostat technology. Student
Housing sought an advanced thermostat strategy that
would improve control of the facilities, simplify mainte-
nance, and reduce energy consumption. In 2011 UC Davis
Student Housing piloted this technology in two residence
halls. Subsequent installations advanced the pilot to
several buildings in 2012, and then rolled the strategy out
to all residence halls on campus in 2013. The measure is
currently installed in more than 3,000 individual residence
hall rooms in 25 separate buildings.
The study began with a review of the system behavior
and energy consumption data for Potter Hall, one of the
first two buildings retrofit. Evaluation of this building was
conducted in parallel with the second phase of instal-
lations, and highlighted the importance of considering
mechanical system design and control characteristics
when applying advanced controls. The building did not
achieve energy savings. While the occupancy sensing
and adaptive thermostat devices functioned as intended,
the research team discovered that due to the physical
design of the building mechanical systems, adjusting the
call for heating and cooling from the thermostat based on
occupancy in each room had practically no effect on ac-
tual systems operations. In fact, it appears that the retrofit
may have resulted in an increase for fan energy consump-
tion. The outcome can be attributed to the fact that each
fan coil serves multiple rooms, and that the operation of
these fan coils is managed in part by the central building
automation system according to temperature in the corri-
dors. This example suggests that integration of advanced
controls must carefully evaluate the specific operating
scheme for the mechanical equipment which it intends to
control. If certain portions of the overarching sequence
of operations managed by some factor other than the
thermostat, improved thermostat controls may have little
bearing on actual system behavior.
Following the pilot at Potter Hall, this study turned at-
tention toward four dormitory buildings in the Segundo
Housing Complex. The four buildings are similar, 5-story
concrete-and-steel structures originally constructed in
1965. In these buildings, each thermostat has direct and
complete control over a fan coil unit dedicated to each
room. This avoids the problems encountered previously
described at Potter. These residence halls each have 110
rooms and various common spaces, such as corridors,
meeting rooms, laundry rooms and bathrooms. Condi-
tioning for the common spaces is served by a central air
handler. Bedrooms occupy about 50% of the total floor
3.0 DEMONSTRATIONS
Ryerson and Bixby dormitory buildings in Davis, California
OCCUPANCY RESPONSIVE THERMOSTATS 8 PROJECT REPORT
area, and are equipped with two-pipe, three-speed fan coil systems for heating and cooling. All rooms are
restricted to either cooling or heating during any given period. Chilled water and steam supplied from the
campus central plant are generally switched only once per season. Fresh air ventilation is provided by cen-
tral exhaust and through operable windows.
The occupancy sensing adaptive thermostats were installed for Bixby Hall in September 2011 as part of the
first pilot phase. Installation in Malcolm, Gilmore and Ryerson followed in May, June and July 2012 respec-
tively. In all cases, the new thermostats replaced unrestricted manual thermostats, but they did not control
the corridors. The research team collected data in cooling seasons and during periods of high and low oc-
cupancy corresponding to the academic quarter and summer conference housing periods (Table 2). Data
included whole building chilled water energy consumption, outside air temperature, occupancy, thermostat
state, active set-point temperature (or set-back temperature), room temperature, and fan coil run time in
every room. Since historical whole-building chilled water energy consumption data was only available for
Ryerson and Gilmore, data from cooling season performance in September – October 2012 (post-installa-
tion) were compared against chilled water energy consumption data from April – May 2012 (pre-installation).
Further, from April 2012 to February 2013, the thermostats in Gilmore and Malcolm were switched between
an occupancy-responsive mode and a conventional operating mode in alternating weeks (ON-OFF). This al-
lowed for comparison both in academic and non-academic periods (Table 2).
Table 2: Data periods utilized for study
Apr
il 20
12
May
20
12
June
20
12
July
20
12
Aug
ust 2
012
Sept
embe
r 20
12
Oct
ober
20
12
Nov
embe
r 20
12
Dec
embe
r 20
12
Janu
ary
2013
Febr
uary
20
13
Mar
ch 2
013
Apr
il 20
13
May
20
13
June
20
13
July
20
13
Aug
ust
2013
Sept
embe
r 20
13
Oct
ober
20
13
Nov
embe
r 20
13
Dec
embe
r 20
13
Janu
ary
2014
Febr
uary
20
14
Mar
ch 2
014
Apr
il 20
14
Ryerson
Gilmore
Malcolm
Bixby
Baseline for cooling operation during academic period (high occupancy)
Post-retrofit for cooling during academic period (high occupancy)
Baseline for cooling during non-academic period (low occupancy)
Post-retrofit for cooling during non -academic period (low occupancy)
Controlled pre -post comparison for cooling, week ON – week OFF during academic period
Controlled pre -post comparison for cooling, week ON – week OFF during non -academic period
Baseline for heating operation during academic period
Post-retrofit for heating operation during academic period
Controlled pre -post comparison for heating, week ON – week OFF during academic period
Data not available
OCCUPANCY RESPONSIVE THERMOSTATS 9 PROJECT REPORT
Summary of Technology AssessmentData analysis used a multiple change-point regression
model to characterize the baseline chilled water and
hot water energy consumption as a function of several
independent variables (outdoor temperature, 24 hour
temperature history, and building occupancy rate). The
methods for pre-post comparison adhered to the prin-
ciples established by ASHRAE Guideline 14: Measure-
ment of Energy and Demand Savings. Measured chilled
water and hot water consumption from each post-retrofit
dataset was compared to a projected baseline that uses
the regression model to predict energy consumption
that a baseline system would have used during the post-
installation conditions. For the experiment that involved
alternating weeks with the occupancy-responsive feature
enabled and disabled, the combination of all weeks with
the feature disabled were used as baseline.
Overall results for chilled water and hot water energy
savings are shown in Table 3. Chilled water savings dur-
ing the academic periods is limited. In fact, there is no
measurable difference during these periods. However
savings exceeds 20% during the summer non-academic
months. These results are restricted to an assessment of
chilled water energy use, and do not estimate the electric
impacts related to fan power in all fan coil units.
It appears that the major difference between savings po-
tential in the academic and non-academic periods is a re-
sult of the fact that occurrences of vacancy in each room
during the non-academic period are more coincident with
vacancy throughout the building. Although whole building
occupancy during the academic period is only 60-70%
on average, the occurrences of vacancy in each room
are more disaggregate and sporadic. For example in the
academic period, some students leave for class for a few
hours, but adjacent rooms tend to remain occupied. The
building may only be 50% occupied, but the distribution
of vacant rooms tends to occur as a checkerboard spread
across the building, and the periods of vacancy in each
room is often too short to allow temperature to drift all
the way to the set-back.
To the contrary, occupancy patterns over the summer
period are more regular, and vacancy in one room is more
likely to correspond to vacancy throughout the building.
During this time, residence halls are used as conference
housing with no permanent residents. Periods of vacancy
tend to be much longer, indoor/outdoor temperature dif-
ference is generally larger, and indoor temperature tends
to drift all the way to the set-back temperature when
rooms are unoccupied. The summer period also experi-
ences periods with much lower occupancy, in fact, aver-
age occupancy during the period is only 10%.
Practically, in the summer a prolonged set-back in 90% of
the rooms produces an effect similar to an increase of the
whole building set-point by a few degrees. We hypoth-
esize that if vacancy in rooms during the academic period
was more prolonged, and more synchronous with vacancy
in adjacent rooms, the same level of whole building aver-
age occupancy would yield greater savings. 10% hot water
savings was realized during the heating academic period.
Building Study Period Savings
Ryerson Pre-post Comparison | Cooling | Spring 2012 vs Fall 2012 | Academic Period 3.4%
Gilmore Pre-Post Comparison | Cooling | Spring 2012 vs Fall 2012 | Academic Period 0.0%
Gilmore Week ON - Week OFF Control | Cooling | Summer 2013 | Non-Academic 29.0%
Malcom Week ON - Week OFF Control | Cooling | Spring 2013 | Academic Period 2.8%
Malcom Week ON - Week OFF Control | Cooling | Summer 2013 | Non-Academic 21.6%
Malcom Pre-Post Comparison, Week ON - Week OFF Control | Cooling | Fall 2013 | Academic Period 6.2%
Malcom Week ON - Week OFF Control | Heating | Winter-Spring 2014 | Academic Period 9.9%
Gilmore Week ON - Week OFF Control | Heating | Winter-Spring 2014 | Academic Period 9.5%
Table 3: Savings calculated during Academic and non-Academic periods
OCCUPANCY RESPONSIVE THERMOSTATS 10 PROJECT REPORT
Telconet Performance Results from 110 buildings at UC Davis
Operation mode Heating Cooling
Occupancy level Low High Low High
H/CW energy in period (kWh) 44,291 198,544 61,163 38,413
Energy Savings 7% 7% 25% 3%
Site Energy savings (kWh) 16,513 16,486
Distribution Efficiency 0.8 0.8
Plant Efficiency 0.8 3
Source Energy Savings (kWh) 25,801 6,869
In terms of project economics, Table 4 shows a generalized project savings and costs estimation for this technology. As
was seen in this project the primary savings were found to be during the summer months when the building experienced
reduced and unpredictable occupancy. The plot shown as Figure 1 illustrates how simple payback changes with changing
utility rates based off a unit cost of $350 each, with a total material and installation cost of 38,500 per building.
Table 4: Performance results for both heating and cooling modes during both high and low occupancy levels
0
2
4
6
8
10
12
14
16
18
$0.05 $0.10 $0.25
Num
ber
of
Yea
rs
Cost per kWh
$0.15 $0.20
Figure 1: Payback vs. Electricity Cost
OCCUPANCY RESPONSIVE THERMOSTATS 11 PROJECT REPORT
Lessons LearnedThe very first installation of this technology in a resi-
dence hall in Davis with a different mechanical system
setup showed low energy savings because the thermo-
stats were not integrated appropriately into the existing
control scheme for the building mechanical system. That
experience serves as a reminder that as the complexity of
building systems increases, minor changes in a sequence
of operations, and small misunderstandings about system
function can have broad impacts on building function that
may counteract energy savings potential.
In the second phase of pilot installations, there were some
minor commissioning challenges with the thermostats
themselves, but no major failings were observed. The
small challenges encountered were all addressed through
software updates. It is worth noting that throughout the
course of this study, the authors have observed multiple
software advances for the technology which have in-
creased reliability, and expanded functionality and
usability.
Proper placement of the occupancy sensors for these sys-
tems is critical. False occupancy readings can be caused
by furniture placement or other obstructions, thermal flow
within the sensors’ field of vision, or activity outside a
window such as passing cars. Experience from installation
at other universities suggests that the ceiling is the best
location to install sensors.
Additional Benefits of the TechnologyIn general UC Davis Student Housing has been pleased
with the thermostat systems and most recently installed
the devices for every residence hall room on campus.
Interestingly, while the system has benefits as an energy
efficiency measure, the asset management functionally
provided seems to be the major driving factor for the
technology. The potential for room-by-room insight to
support diagnostics and troubleshooting, as well as global
control of set-points and schedules for thousands of
rooms from a web interface on a computer are invaluable
capabilities.
There are many applications where occupancy responsive,
adaptive, and otherwise ‘smart’ thermostats can derive
substantial savings and operational benefits. Some of the
applications that might be most appropriate include:
1. Single family homes and apartments (large fraction
of vacancy, wholly controlled mechanical system, and
independent thermal zone dominated by external
loads)
2. Small- and medium-sized businesses – especially
offices (large fraction of vacancy, independently con-
trolled systems, limited thermal interaction between
zones, dominated by external loads).
3. Laboratories – (or other spaces where ventilation
rates can be controlled on an occupancy signal, and
conditioning loads are dominated by outdoor condi-
tions)
4. Hotels, Apartments & Dorms – (large fraction of
vacancy, limited thermal interaction between occu-
pied zones and vacant zones – predict better savings
where vacancy is organized in blocks).
For residence halls connected to central plants in hot and
dry climates like Davis, this study indicates that energy
savings during the summer period is substantial, but
the savings were much less for cooling during academic
periods. Heating savings of around 10% are also signifi-
cant. There may be energy benefits associated with other
features for these thermostats but the occupancy sensing
adaptive algorithms did not result in a measurable impact
at UCD during academic periods. Future studies should
monitor the fan power and energy use controlled by the
thermostats. Broader adoption of the technology for resi-
dence halls requires careful consideration for the specific
application, and measured expectations for the annual
energy savings and operational advantages..
Decisions about where to deploy occupancy responsive
thermostats need to be guided by testing designed to
determine whether or not room temperature will drift
back to the set-back temperature for significant amounts
of time. If cooling loads are merely transferred to adjacent
rooms, and zone temperature does not drift very far, then
occupancy responsive set-back may not capture savings.
4.0 CONCLUSIONS & RECOMMENDATIONS
OCCUPANCY RESPONSIVE THERMOSTATS 12 PROJECT REPORT
This analysis does not capture the potential for savings that is available from improved programming and scheduling
capabilities. This should be estimated separately for any application in question. A large portion of the savings reported
from other residence halls that have installed this technology is suggested to have come from the ability to constrain
set-point limits. Most ‘smart’ thermostats provide networked communications that allow for simple management and set-
point control in hundreds of rooms at once. Further, systems can easily be shifted to extreme set-backs during holidays.
If estimating the potential for savings for future projects, we recommend a number of application-specific characteristics
that should be considered:
1. Mild climates will achieve a smaller magnitude of savings than extreme climates.
2. Application should minimize the number of areas that are not controlled by occupancy responsive functions, espe-
cially when the zones have some thermal interconnection.
3. The technology should be applied where zone-by-zone control can be accomplished, and where doing so does not
result in diminished equipment performance.
4. During academic periods, residence halls operate with a relatively high degree of occupancy, and occurrences for
vacancy are spread across a building in a very irregular and heterogeneous way. When vacant rooms are surrounded
by occupied and conditioned zones, the tendency to drift toward a set-back temperature is diminished – thermal load
for a vacant room in set-back is transferred to adjacent conditioned zones.
5. During academic periods, a large fraction of vacancy events persist for a relatively short time. For short periods of
vacancy, a large fraction of the theoretical savings opportunity is consumed by the energy use required for recovery.
6. The adaptive set-back strategy will have a more significant impact in inefficient buildings, where the indoor load is
more closely coupled to environmental conditions, and a relaxed set-point results in a larger total energy benefit.
Buildings with large ventilation conditioning load are also good candidate for this technology.
7. Quick and easy tests should help to identify savings potential for the building:
a. Test rooms proposed for occupancy responsive controls by adjusting set-point and observing thermal behavior.
If the temperature does not drift to a set-back then there is little opportunity for savings (other mechanisms are
conditioning the zone).
b. Consider occupancy throughout the year. Long periods of vacancy, or low average occupancy offer larger
savings opportunity. If vacancy periods align with periods of peak conditioning requirements, the building has
more potential savings.
OCCUPANCY RESPONSIVE THERMOSTATS 13 PROJECT REPORT
Over the course of the effort to evaluate occupancy sensing adaptive thermostat controls, Western Cooling
Efficiency Center and CIEE have published a number of different reports and papers that address different
aspects of the research findings and technology opportunity.
1. Occupancy Sensing Adaptive Thermostat Controls – A Market Review and Observations from Multiple Field Installations in University Residence Halls (Woolley, Peffer ACEEE 2012)
• Presents a framework for characterizing advanced thermostat control strategies (classification,
market and cost assessment)
• Discusses range of target applications for adaptive thermostat technologies (hotels, residence
halls, conference or assembly halls are good candidates)
• Examines challenges encountered with application in one residence hall (Potter)
• Presents preliminary results from another installation (Bixby), indicating that reduction in
equipment runtime for each room during vacant periods is significant.
2. CIEE Technical Report: Advanced Thermostat Controls (Johnson, Peffer, Woolley, SPEED report 2012)
• Presents a general description and background of currently available thermostat technologies,
including occupancy-sensing, advanced algorithms, engaging interfaces and networked systems.
• Describes anecdotal results from two field installations of occupancy-sensing thermostats in
residence at other universities
• Concludes this technology has opportunities, but there are not enough field studies measuring
savings.
3. Occupancy Sensing Adaptive Thermostat Controls for University Residence Halls (Pritoni, Woolley, Mande, Modera. prepared for Journal publication)
• Explores the relationship between Telkonet system behavior and whole building chilled water use
and dynamics
• Discusses parameters that have an impact on room temperature and runtime reduction
• Calculates savings in Bixby for pre-post retrofit: 30% during fall-spring cooling season
• Calculates the impact of occupancy-sensing feature on energy use. The impact is large, but there is
uncertainty what portion of this savings is related to reduced internal gains, and what portion can
be attributed to the thermostat control features.
5.0 RELATED RESOURCES & REVIEW OF PROJECT OUTCOMES
OCCUPANCY RESPONSIVE THERMOSTATS 14 PROJECT REPORT
6.0 CollaboratorsUC Davis Facilities Management funded the purchase of the Telconet Thermostats and commissioning. California Institute
for Energy and Environment, UC Davis Western Cooling Efficiency Center, provided project management, technical guid-
ance, and performance evaluation.
Any questions about this project, including technology costs, can be directed to:
For more resources and information, including technology catalogs, business case studies and demonstration maps, visit PARTNERSHIPDEMONSTRATIONS.ORG.
JONATHAN WOOLLEYUC Davis
Western Cooling Efficiency Center
wcec.ucdavis.edu
KARL JOHNSONCalifornia Institute for Energy and Environment
uc-ciee.org
4. Why Occupancy-Sensing Adaptive Thermostats Do Not Always Save - and the Limits for When They Should (Woolley, Pritoni, Peffer ACEEE 2014)
• Shows results for several well controlled pre-post and ON-OFF experiments on four more buildings during
2012-2014. Chilled water savings are close to zero during the spring-fall academic period and around 20% in
the summer non-academic period.
• Presents a theoretical framework and a simulation model to understand the impact of set-back strategies
• Reviews additional studies in the literature
• Provides recommendations on the selection and installation of this technology
MARCO PRITONIUC Davis
Western Cooling Efficiency Center
wcec.ucdavis.edu